initial commit

.gitignore

@@ -0,0 +1 @@
+__pycache__

app.py

@@ -1,80 +1,29 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-import gen 
+import gen
 import psychohistory
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-
-
 with gr.Blocks(title="PSYCHOHISTORY") as app:
-
-
     with gr.Tab("Search"):
         with gr.Row():
-            txt_search = gr.Textbox(value="Iran and Israel war",label="Search Term",scale=5)
-            btn_search = gr.Button("Look",scale=1)
+            txt_search = gr.Textbox(value="Iran and Israel war", label="Search Term", scale=5)
+            btn_search = gr.Button("Look", scale=1)
         with gr.Row():
-            #search_results = gr.Dataframe(type="pandas")
             mem_results = gr.JSON(label="Results")
             btn_search.click(
-                gen.generate, 
+                gen.generate,
                 inputs=[txt_search],
                 outputs=mem_results
-            )  
-            
-        #with gr.Row():
-        #    big_block = gr.HTML("""
-         #       <iframe style="scroll-padding-left: 50%; relative;background-color: #fff; height: 75vh; width: 100%; overflow-y: hidden; overflow-x: hidden;" src="https://holmesbot.com/api/shared?id=16657e456d9514"></iframe>
-         #   """)
-        
-    with gr.Tab("Graph"):
-        gr.load("models/stabilityai/stable-diffusion-xl-base-1.0")
-    with gr.Tab("Chat"):
-        
-        gr.ChatInterface(
-            respond,
-        )
+            )
+
+        with gr.Row():
+            img_output = gr.Image(label="Graph Visualization", type="filepath")  # Add an Image component
 
+            # Trigger graph generation after JSON is generated
+            mem_results.change(
+                psychohistory.main,
+                inputs=[mem_results],
+                outputs=img_output
+            )
 
 if __name__ == "__main__":
-    app.launch()
+    app.launch()

psychohistory.py

@@ -156,8 +156,9 @@ def draw_global_tree_3d(G, filename='global_tree.png'):
     plt.savefig(filename, bbox_inches='tight')
     plt.close()
 
-def main(mode, input_file=None):
+def main(json_data):
     G = nx.DiGraph()
+    build_graph_from_json(json_data, G)
 
     if mode == 'random':
         generate_tree(0, 0, 0, 5, 3, 10, G)
@@ -169,7 +170,7 @@ def main(mode, input_file=None):
         print("Invalid mode or input file not provided.")
         return
 
-    draw_global_tree_3d(G)
+    draw_global_tree_3d(G, filename='global_tree.png')
 
     best_path, best_mean_prob, worst_path, worst_mean_prob, longest_path, shortest_path = find_paths(G)
 
@@ -186,7 +187,7 @@ def main(mode, input_file=None):
         print(f"\nPath with the shortest duration: {' -> '.join(map(str, shortest_path))}")
         print(f"Duration: {max(G.nodes[node]['pos'][0] for node in shortest_path) - min(G.nodes[node]['pos'][0] for node in shortest_path):.2f}")
 
-    draw_global_tree_3d(G)
+    draw_global_tree_3d(G, filename='global_tree.png')
 
     if best_path:
         draw_path_3d(G, best_path, 'best_path.png', 'blue')
@@ -197,6 +198,8 @@ def main(mode, input_file=None):
     if shortest_path:
         draw_path_3d(G, shortest_path, 'shortest_duration_path.png', 'purple')
 
+    return 'global_tree.png'
+
 
 if __name__ == "__main__":
     if len(sys.argv) < 2: